Providing quality health care and related services (e.g., pharmaceutical services, veterinary services) depends on having the ability to reliably access various types of records. In the case of patients, information regarding a particular patient may be needed by various different types of health care related entities. For example, any one of a hospital, a health care organization, a clinic, a clinical or hospital lab, an insurance company, or a pharmacy may need access to particular computerized patient information. Such information retrieval generally occurs by querying a database associated with the health care related entity performing the query. The database typically contains all or part of what is referred to as a “Master Patient Index” (MPI), which is a collection of patient information and identifiers. Particularly, an MPI is a collection of indexed patient records, where each record contains information about a particular patient. In practice, user-level applications submit known or believed patient information to the database, which then uses the MPI to match the incoming data with information stored in the database. If a match is found, the record (or pointer thereto) is returned to the querying entity. If the patient cannot be matched, the MPI creates a new patient record.
While a typical MPI is designed to work within or for a particular health care related entity (e.g., a single hospital, a medical group), including among disparate information systems across the health care related entity, the increased mobility of individuals throughout the overall health care system and the constant evolution of health care in general requires that patient information be reliably accessible by a local, state, regional, or national community of health care related entities. Reaching this goal is further complicated by the presence of political issues among entities and the lack of cooperation between competing entities.
One possible way to achieve community-wide access is to use a centralized MPI, whereby separate health care related entities would patient match using the same centralized MPI. However, such a centralized MPI may prove to be flawed, or at least non-optimal, in view of the fact that different health care related entities have different ways of configuring, submitting, searching for, and handling patient information. For example, one health care related entity could have policies in place or be configured to enter all ‘1’s in a social security field of a query when the social security number of a patient is unknown, whereas another health care related entity could have policies in place or be configured to enter ‘123-45-6789’ for an unknown social security number. Thus, when configuring the centralized MPI, algorithm adjustments aimed to improve a matching accuracy for one health care related entity could come at the expense of reducing matching accuracy for another health care related entity. Accordingly, because of such a “win/loss” effect, otherwise potential benefits of using a centralized MPI are compromised.
Another way to “share” patient information involves the use of an electronic data interchange (EDI). EDI allows entities to transfer data according to prescribed business standards. However, although EDI can be used to share patient information, EDI is not helpful for determining the identity of a patient based on incomplete or ambiguous information. In other words, EDI poorly supports, if at all, reliably matching queries with patient records.